Information for Prospective Students or Post-Docs in the Lab of Prof. John K. Kruschke

* New graduate student sought for August 2017 *

Research Topics: I am interested in the science of moral judgment, broadly construed. Moral psychology encompasses a panorama of topics, and I am open to considering projects across the spectrum. Ongoing projects include research into how people decide to punish freeloaders, how people evaluate police use of force, and how people's moral sensitivities affect perceived humor. Past projects included research into the role of moral judgment in literary narrative. I am also interested in norm acquisition, the inference of agent intention, the role of emotion in moral judgment, etc. New projects could be purely empirical, but I am keen to involve computer modeling, for example with Bayesian networks, evolutionary models, reinforcement learning, etc. Much (okay, most) of my time is also devoted to applications, teaching, and dissemination of Bayesian data analysis. Research into statistical methods per se is not my primary focus, but could emerge as a side project.

Research Culture: I encourage interdisciplinary topics and interdisciplinary collaborations. If we develop a project that would naturally involve some other faculty, I am eager to include them. Indiana University has a culture of active and cordial interdisciplinary collaboration among many faculty across various programs, departments, and schools, including the Cognitive Science program. Within my own lab, I am keenly aware of the need for reproducible research with methodological rigor not just flash. (Here's a link to one of my blog posts, on the topic of Bayesian approaches to replication analysis.)

Qualities sought in students. I am looking for student collaborators who have a demonstrated interest in moral psychology, and who can eagerly and efficiently digest a vast literature. I encourage applications from students who have interests bridging into other fields; that is, moral psychology applied to other domains, or moral psychology through the lens of other perspectives. A successful student forges ahead independently and has excellent time-management skills. Students should also have a strong interest in Bayesian data analysis, along with strong skills in computer programming, and in mathematics too. Such skills can be learned and developed in graduate school, but it helps to have previous experience. Computer programming is needed for computerized experiments, data analysis, and computational models. We use software such as R, jsPsych, javascript, Python, JAGS, Stan, etc. Mathematical savvy is also important for understanding statistical and computational models, even if the primary focus is on empirical research.

About me (Prof. Kruschke): A brief biography can be found here. For more information about my publications, see this page. Contact information is here or here. For less information, click here.

Your funding: If you are admitted to the Department of Psychological and Brain Sciences, you are guaranteed five years of funding as a teaching assistant. You will also apply for external fellowships, guided by a first-year professional development course.

Interested in applying to be a graduate student?The application deadline is December 1, 2016. The Indiana University graduate school admissions web site is here. When you apply to the Department of Psychological and Brain Sciences, mention me as one of the faculty with whom you would be interested in working, to be sure I see your application. Also, you may want to apply simultaneously to another department such as the Cognitive Science Program. You could have the Cog Sci Program as your primary department instead of the Dept of Psych and Brain Sci but still work with me as your primary mentor because I am in the core faculty of the Cog Sci program. Even if you don't apply to the Cognitive Science program for admission, most of the students who work with me from Psych and Brain Sci are double majors in the Cog Sci program.

Some students or post-docs with whom I have published, or expect to soon:

Emily Kappenman
B.S. with Honors, 2005.
Emily was co-advised by Bill Hetrick. Emily won the Psychology
Department's J. R. Kantor Award for excellence in undergraduate
research, and subsequently won an NSF Graduate Fellowship. In graduate
school she worked with Steve Luck at the University of California at
Davis.

Nate Blair
Ph.D. 2001.
Nate did post-doctoral research with Barbara Dosher at the University of California at Irvine. Then he became a Lecturer in the Dept of Psychology at California State University Sacramento.

Teresa Treat
Ph.D. 2000.
Teresa's primary mentor was Dick McFall, but Teresa devoted a lot of
energy to our lab too. After a clinical intership, she joined
the faculty of Yale University, and then the faculty of the University of Iowa.

Michael Erickson
Ph.D. 1999. Outstanding Dissertation Award from the I.U. Cognitive
Science Program.
Michael did post-doctoral research with Lynne Reder and then Jay
McClelland at Carnegie Mellon University. Michael then joined the faculty
of the University of California at Riverside, and then the faculty of
Hawaii Pacific University.

Mike Kalish
Post-doctoral researcher, 1993-1995.
Mike then joined the faculty of the University of Western Australia,
Perth, then the University of Louisiana at Lafayette, and then Syracuse University.

My (Kruschke's) graduate mentor was Prof. Stephen Palmer, University of California at Berkeley, during the years 1983-1989. Steve was tremendously supportive and encouraging of my intellectual pursuits. He showed me repeatedly --by example and by direct instruction-- what it meant to think rigorously and incisively, and what it meant to write and present clearly. (BTW, his textbook, Vision Science, is nothing less than monumental and shows the clarity and scope of his teaching.) He was perspicacious enough to teach a seminar regarding the just-published PDP (parallel distributed processing, a.k.a. connectionism) books, which became a launching pad for my subsequent ideas. I worked hard on a number of projects with Steve (regarding reference frames in shape perception), and with Danny Kahneman and Anne Triesman and John Watson (regarding perception of causality). Unfortunately, none of the projects produced data that were publishable! The lack of publications meant that Steve's support was all the more crucial. Danny Kahneman told me, as I was fearfully sending out job applications, "At this point Steve can do more for you than you can do for you." Thanks Steve!